AIMC Topic: CA-125 Antigen

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Employing AgNPs doped amidoxime-modified polyacrylonitrile (PAN-oxime) nanofibers for target induced strand displacement-based electrochemical aptasensing of CA125 in ovarian cancer patients.

Materials science & engineering. C, Materials for biological applications
In this study, a high-performance biosensing nanoplatform based on amidoxime-modified polyacrylonitrile nanofibers decorated with Ag nanoparticles (AgNPs-PAN-oxime NFs) is described. The AgNPs-PAN-oxime NFs were prepared by the combination of electro...

High-Grade Serous Ovarian Cancer: Use of Machine Learning to Predict Abdominopelvic Recurrence on CT on the Basis of Serial Cancer Antigen 125 Levels.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to use machine learning to predict abdominal recurrence on CT on the basis of serial cancer antigen 125 (CA125) levels in patients with advanced high-grade serous ovarian cancer on surveillance.

Ultrasensitive flexible FET-type aptasensor for CA 125 cancer marker detection based on carboxylated multiwalled carbon nanotubes immobilized onto reduced graphene oxide film.

Analytica chimica acta
The development of a novel flexible and ultrasensitive aptasensor based on carboxylated multiwalled carbon nanotubes (MWCNTs)/ reduced graphene oxide-based field effect transistor (FET) has been reported for label-free detection of the ovarian cancer...

A novel algorithm to improve specificity in ovarian cancer detection.

Cancer treatment and research communications
BACKGROUND: Measurement of autoantibodies (AAbs) to tumor associated antigens has been proposed to aid in the early detection of ovarian cancer with high specificity. Here we describe a multiplex approach to evaluate selected peptide epitopes of p53 ...

Preoperative assessment of lymph node metastasis in endometrial cancer: A Korean Gynecologic Oncology Group study.

Cancer
BACKGROUND: Previously proposed criteria for preoperatively identifying endometrial cancer patients at low risk for lymph node metastasis remain to be verified. For this purpose, a prospective, multicenter observational study was performed.

Models of logistic regression analysis, support vector machine, and back-propagation neural network based on serum tumor markers in colorectal cancer diagnosis.

Genetics and molecular research : GMR
We evaluated the application of three machine learning algorithms, including logistic regression, support vector machine and back-propagation neural network, for diagnosing congenital heart disease and colorectal cancer. By inspecting related serum t...

Exploring Ovarian Cancer Prediction Models and Potential Markers Using Machine Learning.

Annals of clinical and laboratory science
OBJECTIVE: To develop machine learning models, facilitate a more accurate diagnosis of ovarian cancer (OC), and explore potential markers.

Evaluation of Combined Cancer Markers With Lactate Dehydrogenase and Application of Machine Learning Algorithms for Differentiating Benign Disease From Malignant Ovarian Cancer.

Cancer control : journal of the Moffitt Cancer Center
BACKGROUND: The differential diagnosis of ovarian cancer is important, and there has been ongoing research to identify biomarkers with higher performance. This study aimed to evaluate the diagnostic utility of combinations of cancer markers classifie...